Visualizing categorical data

Towards the end of this chapter, let's try to integrate all datasets that we have processed so far. Remember that we briefly introduced the three categories of population structures (that is, constrictive, stable, and expansive) earlier in this chapter?

In this section, we are going to implement a naive algorithm for classifying populations into one of the three categories. After that, we will explore different techniques of visualizing categorical data.

Most references online discuss visual classification of population pyramids only (for example, https://www.populationeducation.org/content/what-are-different-types-population-pyramids). Clustering-based methods do exist (for example, Korenjak-Cˇ erne, Kejžar, Batagelj (2008). Clustering of Population Pyramids. Informatica. 32.), but to date, mathematical definitions of population categories are scarcely discussed. We will build a naive classifier based on the ratio of populations between "0-4" and "50-54" age groups...